The following are notes from last weeks community of practice call. The
notes will also be posted on the website. Thank you to all who participated.
The topic for next months call will be Tools for marketing the post-school
outcomes survey and examining the adequacy of your current survey. We are
looking forward to hearing from states on next months call.
Community of Practice January 13, 2011
Participants
Dan Boomer [California], Judy Johns [Kentucky], Patti Johnson [Oregon],
Jackie Burr [Oregon], Jennifer Kane [Nevada], Bobby Grammar [North
Carolina], Eudora Watson [New York] Deborah Donovan [Mississippi], Susan
Loving [Utah], Amy Jinks [New Hampshire] ,
[NPSO] Ryan Kellems Deanne Unruh Dawn Rowe Jim Leinen
Please let us know if we misspelled your name or didn¹t include you on the
list!
Notes are not verbatim but rather an attempt to capture the essence of what
is shared. Please alert us if there are glaring errors!
Announcements & Reminders:
NPSO I-14 Data Use Toolkit Training: March 1-2, 2011
Secondary Transition State Planning Institute: May 17-21, 2011
Topic: Response Rate, Why are students not engaged and how have you reached
those hard to reach populations?
Welcome. My name is Dawn Rowe. I am the project coordinator for NPSO. I
started this position just this past November, so I am relatively new to
this project. I am not new to the field of transition however. I am
finishing up my doctoral work at the University of North Carolina at
Charlotte and have worked with NSTTAC for the past two and half years. Prior
to that I was a transition specialist for a local school district in South
Carolina.
Thank you all for calling in. Today I will be facilitating a conversation
about your SPP/APR analysis and what you have learned about students who are
leaving high school, particularly students who fall into the non-engaged
group. I encourage you to share information you have obtained about who
falls into the non-engaged group and improvement activities that are being
developed to reduce the numbers of individuals who fall into this category.
We will also discuss the your response rate to I-14 data collection and
strategies for reaching those hard-to-reach populations. So let¹s get
started.
Many of you have either completed the SPP/APRs or are putting the final
touches on them prior to sending them to OSEP. You should now have an idea
of who are employed, who are enrolled in higher education, who fall into the
some other employment category and who falls into the some other
postsecondary education group. Lets begin by hearing about some of your
outcomes.
What was the outcome that stood out most in your SPP/APR analysis? Share one
positive outcome and maybe one that was somewhat shocking.
NH: The response rates from students with LD and ED were better than
anticipated. We had a slightly lower response rate due to undeliverable
surveys. We¹ll need to work on that.
UT: We had more students in the postsecondary education category than in
employment. We have found it challenging to explain what is going on with
students using the ABC definitions required in the SPP/APR. When we are
sharing data with public we have to explain what ³other² means.
CA: We had a high response rate (94%)
MS: Our response rate was 87%. The number reported enrolled in some other
education or some other employment was small. These were the lowest
percentages we had.
NY: We had a decrease in response rate this year. The numbers we could reach
were down this year. Our male to female ratio was what we expected. We had
more females than males.
NC: Our response rate was down. Measurement C was highest area. Our students
are engaged in something. We provide intensive job training prior to leaving
high school, which helps with competitive employment. The majority of our
students going to postsecondary education are going to community colleges.
NV: We have changed systems for collecting I-14 data. We are still working
on our data poll.
KY: We had a 61% response rate. 39% of those were not engaged and 28% were
employed.
OR: Our response rate was low about 72%. We had more individuals working
than in higher education. We had a smaller other category. Our biggest
districts are not as engaged in the process as the smaller districts.
CA: 2400 students in community college. 5000 in some type of other
postsecondary education. 3700 employed. We were not able to contact about
14,000.
Have you drilled into your data to determine what is happening with the
non-engaged group? What will you do with this information? How will you use
this information to develop improvement activities? What types of
improvement activities have you got planned to reduce the non-engaged group?
UT: We got a lot of responses like he has a disability so he can¹t work or
he can¹t go to college. The parent and student expectations are low. We need
to look into increasing these expectations prior to leaving high school and
looking at the impact of disability on employment and postsecondary
education. Provide more support.
CA: Saying ³I can¹t² was a big NO NO in front of my Dad.
NY: We have One-stop centers and other services providers that provide a
multitude of services; however, awareness of programs and supports available
after an individual leaves high school was low.
NC: We had lots of ³I don¹t know² responses. SSI was the most well known
service provided. We have a huge partnership with VR, but this was fairly
low on the list. Getting accurate information from the larger districts is a
challenge.
OR: We have taken a case study approach to reporting information back to the
LEA¹s. We do a pre-exit survey. Districts are able to look at individual
student outcomes and transition services and supports provided.
NH: We need to look at questions to be able to then look further into the
non-engaged group. We had lots of people who did not complete the item and
we did not ask any other questions that would allow us to drill further. As
far as improvement activities, we are focusing on I-13 and providing better
transition services in school to improve post-school outcomes. We also had
an issue with the 90 days question. Lots of students were employed but not
for 90 days and we did not have questions to learn why.
UT: Bad numbers
CA: I am looking at breaking down the question to not able to contact the
first time and not able to contact the second time and look at the response
rate that way. If you take out the other category the response rate went up.
What was your response rate?
See above responses as well
UT: We had a 20% response rate. 80% could not be contacted or did not answer
the survey. We had lots of bad numbers and disconnected numbers.
OR: We had lots more disconnected numbers or people who did not want to
participate. We think it is due to the economy. We do a phone survey and
people are not answering the phone. Many people have debt collectors
calling and are just not answering.
NV: When we just did a hard copy of the survey we had a higher response
rate. We now give people options to participate. They can participate by
phone, snail mail, or online. We thought that the use of technology would
improve our response rate because it was easier to complete the survey but
it did not happen. We think it is because previously parents were responding
to the surveys on behalf of their students. Students are not responding at
the same rate as their parents. Plus we have had lots of kinks in our new
system to work out.
NY: We get many more phone numbers now. Many are disconnected. We offer a
web version of the survey but very few use this option. We just try to
collect as many number as possible in order to reach them.
NH: We offer a hard copy of the survey and one online. Few students take the
online survey. We met with our stakeholders and they suggested getting
parent emails. Students get so many emails they just want click on
especially if it hasn¹t worked prior. We also have lots of rural areas that
do not have email access.
How are states currently reaching those hard to reach populations?
UT: We continue to do telephone surveys
OR: Our strategy is to get as much information the year before a student
leaves as possible. We have suggested they get this information as an
activity in the classroom. Those who have gotten the information a year
ahead of time have a better rate of response than those who do not.
NV: We have a similar process.
KY: We do a senior survey and are talking about linking the exit survey, the
senior survey, and the individual learning plans so that were are collecting
this information once rather than from multiple sources.
NV: We also conduct a senior survey. I also do a district poll and pull
information from the statewide database to ensure I have the most up-to-date
information.
UT: We do not do any other type of survey.
CA: We had 29, 500 leavers this last year. We rely on the SELPAs to collect
data.
NY: We are using our transition coordinators and trying to provide them with
concrete information and a means to work with districts.
UT: We have a very mobile population. Many of these are also low income and
have the highest drop-out rate. How do we deal with this?
NY: Our minorities were not represented.
UT: Minorities were represented; however, we have a growing refugee
population we are going to have to consider. Lots of barriers to reaching
that group. With the huge variations in languages and dialect it is
impossible to translate all your material.
Our time has come to an end. I appreciate your participation in today¹s
call. I will post notes for today¹s call on the website shortly. Just a
reminder, we are available to review your SPP/APR¹s if needed. Just send
them our way. Our next call will be February 10th. We will be talking about
tools for marketing the post-schools outcome survey and examining the
adequacy of your current survey. We look forward to your participation.
Have a wonderful day.
--
Dawn A. Rowe
Project Coordinator
National Post-School Outcome Center
University of Oregon
541-346-8412
[email protected]
www.psocenter.org
